时态拟序数据索引TQD-tree更新技术

Updating Technique of Temporal Quasi-Order Data Index

为达到大数据管理框架中实时响应和频繁更新的基本需求,基于线序划分(LOP)的时态数据索引TQD-tree,研究了增量更新技术,提出了新的增量插入更新算法,讨论了利用该算法实现批量更新的可行性,并完成仿真评估以证明TQD-tree更新技术的可行性和有效性.仿真结果表明:本增量更新算法能实现批量更新,减少扫描重构TQD-tree次数,大大提高系统效率.

In order to achieve the basic requirements of real-time response and frequent update in big data management framework,on the basis of a temporal data index TQD-tree which is based on Line Order Partition (LOP),the incremental updating technique is researched,a new incremental insertion update algorithm is proposed,and the feasibility of batch update with the algorithm are discussed. Finally,simulative evaluation is conducted to test the feasibility and effectiveness of the TQD-tree updating technology. According to the results of simulative evaluation,the incremental update algorithm achieves batch update,reduces the number of scanning and reconstructing TQD-tree,and improves the efficiency of the system greatly.